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Virtual digital subtraction angiography using multizone patch-based U-Net

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Abstract

Digital subtraction angiography (DSA) is a powerful technique for visualizing blood vessels from X-ray images. However, the subtraction images obtained with this technique suffer from artifacts caused by patient motion. To avoid these artifacts, a new method called “Virtual DSA” is proposed, which generates DSA images directly from a single live image without using a mask image. The proposed Virtual DSA method was developed using the U-Net deep learning architecture. In the proposed method, a virtual DSA image only containing the extracted blood vessels was generated by inputting a single live image into U-Net. To extract the blood vessels more accurately, U-Net operates on each small area via a patch-based process. In addition, a different network was used for each zone to use the local information. The evaluation of the live images of the head confirmed accurate blood vessel extraction without artifacts in the virtual DSA image generated with the proposed method. In this study, the NMSE, PSNR, and SSIM indices were 8.58%, 33.86 dB, and 0.829, respectively. These results indicate that the proposed method can visualize blood vessels without motion artifacts from a single live image.

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Authors and Affiliations

  1. Graduate School of Health Sciences, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake-city, Aichi, 470-1192, Japan

    Ryusei Kimura, Atsushi Teramoto & Kuniaki Saito

  2. Fujita Health University Bantane Hospital, 3-6-10 Otobashi Nakagawa-ku, Nagoya-city, Aichi, 454-8509, Japan

    Tomoyuki Ohno

  3. Faculty of Engineering, Gifu University, 1-1 Yanagido, Gifu-city, Gifu, 501-1194, Japan

    Hiroshi Fujita

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  1. Ryusei Kimura
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  2. Atsushi Teramoto
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  3. Tomoyuki Ohno
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  4. Kuniaki Saito
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  5. Hiroshi Fujita
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Correspondence to Atsushi Teramoto.

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Kimura, R., Teramoto, A., Ohno, T. et al. Virtual digital subtraction angiography using multizone patch-based U-Net. Phys Eng Sci Med 43, 1305–1315 (2020). https://doi.org/10.1007/s13246-020-00933-9

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